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Reassessing Data Quality for Information Products

Author

Listed:
  • Debabrata Dey

    () (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Subodha Kumar

    () (Mays Business School, Texas A& M University, College Station, Texas 77843)

Abstract

The quality profile of information retrieved from a database using a query is quite important in the context of managerial decision making. Parssian et al. (Parssian, A., S. Sarkar, V. S. Jacob. 2004. Assessing data quality for information products: Impact of selection, projection, and Cartesian product. Management Sci. 50(7) 967-982) propose a methodology to determine the quality profile of the result of a query from the quality profile of the source data. Although they consider an important problem, and the proposed methodology is quite useful in practice, some of their results for the selection operation are not correct in general. Here, we identify these errors and present appropriate corrections.

Suggested Citation

  • Debabrata Dey & Subodha Kumar, 2010. "Reassessing Data Quality for Information Products," Management Science, INFORMS, vol. 56(12), pages 2316-2322, December.
  • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:12:p:2316-2322
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    File URL: http://dx.doi.org/10.1287/mnsc.1100.1261
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    References listed on IDEAS

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    1. Amir Parssian & Sumit Sarkar & Varghese S. Jacob, 2004. "Assessing Data Quality for Information Products: Impact of Selection, Projection, and Cartesian Product," Management Science, INFORMS, vol. 50(7), pages 967-982, July.
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    Cited by:

    1. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.

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